减少蛋白质远程同源性检测中简并模式的空间

M. Comin, Davide Verzotto
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引用次数: 0

摘要

在生物学中,简并模式的概念在描述各种现象时起着核心作用。例如,蛋白质活性位点模式,如PROSITE数据库中包含的[FY]DPC[LIM][ASG]C[ASG],通常由具有字符类的退化模式表示。多年来,研究人员开发了几种方法来发现退化模式。尽管这些方法已经在基因组和蛋白质上进行了详尽和成功的测试,但它们的结果往往远远超过了原始输入的大小,使得输出难以管理,然后需要人工检查的精细分析来解释。在本文中,我们讨论了退化模式的特征与字符类,并引入了模式优先级的概念,用于比较和排序不同的模式没有差距,以及底层模式的类,它允许过滤任何一组退化模式到一个新的集合,在输入序列的大小是线性的。我们提出了一些初步结果检测微妙信号的蛋白质序列与远程同源。结果表明,我们的方法大大减少了蛋白质序列分析工具输出的模式数量,同时保留了功能模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing the Space of Degenerate Patterns in Protein Remote Homology Detection
In biology the notion of degenerate pattern plays a central role for describing various phenomena. For example, protein active site patterns, like those contained in the PROSITE database, e.g. [FY]DPC[LIM][ASG]C[ASG], are in general represented by degenerate patterns with character classes. Researchers have developed several approaches over the years to discover degenerate patterns. Although these methods have been exhaustively and successfully tested on genomes and proteins, their outcome often far exceeds the size of the original input, making the output hard to be managed and then interpreted by refined analysis requiring manual inspection. In this article we discuss a characterization of degenerate patterns with character classes, and introduce the concept of pattern priority, for comparing and ranking different patterns without gaps, together with the class of underlying patterns, which permits to filter any set of degenerate patterns into a new set that is linear in the size of the input sequence. We present some preliminary results on the detection of subtle signals in protein sequences with remote homologies. Results show that our approach drastically reduces the number of patterns in output from a tool for protein sequence analysis, while retaining the functional ones.
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